• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.3
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• pp.69-77
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• 2015

MANET is composed of only the mobile nodes have a limited transmission range. The dynamic topology by the frequent movement of nodes makes routing difficult and is also cause exposed to security vulnerabilities. In this paper, we propose the security routing technique consisted of mechanism of two steps in order to respond effectively to attack by the modification of the routing information and transmit secure data. The hierarchical structure is used and the authentication node that issues the key of the nodes within each cluster is elected in this proposed method. The authentication node manages key issues and issued information for encrypting the routing information from the source node. The reliability value for each node is managed to routing trust table in order to secure data transmission. In the first step, the route discovery is performed using this after the routing information is encrypted using the key issued by the authentication node. In the second step, the average reliability value of the node in the found path is calculated. And the safety of the data transmission is improved after the average reliability value selects the highest path. The improved performance of the proposed method in this paper was confirmed through comparative experiments with CBSR and SEER. It was confirmed a better performance in the transmission delay, the amount of the control packet, and the packet transmission success ratio.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.4
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• pp.41-49
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• 2008

Sensor networks are often deployed in unattended environments, thus leaving these networks vulnerable to false data injection attacks in which an adversary injects forged reports into the network through compromised nodes. Such attacks by compromised sensors can cause not only false alarms but also the depletion of the finite amount of energy in a battery powered network. In order to reduce damage from these attacks, several security solutions have been proposed. Researchers have also proposed some techniques to increase the energy-efficiency of such security solutions. In this paper, we propose a CH(Cluster Header) selection algorithm to choose low power delivery method in sensor networks. The CNP(Contract Net Protocol), which is an approach to solve distribution problems, is applied to choose CHs for event sensing. As a result of employing CNP, the proposed method can prevent dropping of sensing reports with an insufficient number of message authentication codes during the forwarding process, and is efficient in terms of energy saving.

• The Plant Pathology Journal
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• v.16 no.4
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• pp.189-199
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• 2000

To search for the antifungal substances, various actino-mycete isolates were obtained from various soils of Korea using plate dilution method on the humic acid vitamin agar plates. In the screening procedures using a dual culture method, 32 actionomycete isolates were selected, which showed the inhibitory activity against mycelial growth of plant pathogenic fungi Altirnaria mali, Colletotrichum gloeosporides, Fusarium oxysporum f.sp. cucumerinum, Magnaporthe grisea, Phytophthora capsici, and Rhizoctonia solani. Bioassay of the crude extracts from culture filtrates and mycelial mets revealed that 12 antagonistic actionomycetes produced highly active antifungal substances. Actinomycete strain S5-55 which showed the substantial antifungal activity against the tested fungi was selected for production of the antifungal substances. Based on the cytochemical and morphological characteristics, strain S5-55 was identified as a Streptomyces species. The results of the numerical identification using the TAXON program confirmed that Streptomyces strain S5-55 was identical with Streptomyces humidus including in TAXON major cluster 19. The production of antifungal substance was most favorable when S. humidus strain S5-55 was cultivated for 10 dats on soluble starch broth supplemented with $K_2$HPO$_4$. The antifungal substances active against the plant pathogenic fungi P. capsici and M. grisea were partially purified using $\textrm{C}_{18}$ reversed-phase column chromatography.

• Journal of Microbiology
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• v.33 no.2
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• pp.136-141
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• 1995

From a cluster of structural rRNA genes which has previsouly been cloned (Hwang and Kim, in submission; J. Microbiol. Biotechnol.), a 1.0-kb Eco RI fragment of DNA which shows significant homology to the 25S and rRNA s of Tricholoma matsutake was used for sequence analysis. Nucleotide sequence was bidirectionally determined using delection series of the DNA fragment. Comparing the resultant 1016-base sequence with sequences in the database, both the 3'end of 25S-rRNA gene and 5S rRNA gene were searched. The 5S rRNA gene is 118-bp in length and is located 158-bp downstream of 3'end of the 25S rRNA gene. IGSI and IGS2 (partial) sequences are also contained in the fragment. Multiple alignment of the 5S rRNA sequences was carried out with 5S rRNA sequences from some members of the subdivision Basidiomycotina obtained from the database. Polygenetic analysis with distance matrix established by Kimura's 2-parameter method and phylogenetic tree by UPGMA method proposed that T. matsutake is closely related to efibulobasidium allbescens. Secondary structure of 5S rRNA was also hypothesized to show similar topology with its generally accepted eukaryotic counterpart.

• Korean Journal of Computational Design and Engineering
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• v.13 no.1
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• pp.1-7
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• 2008

Data compression becomes increasingly an important issue for reducing data storage spaces as well as transmis-sion time in network environments. In 3D geometric models, the normal vectors of faces or meshes take a major portion of the data so that the compression of the vectors, which involves the trade off between the distortion of the images and compression ratios, plays a key role in reducing the size of the models. So, raising the compression ratio when the normal vector is compressed and minimizing the visual distortion of shape model's shading after compression are important. According to the recent papers, normal vector compression is useful to heighten com-pression ratio and to improve memory efficiency. But, the study about distortion of shading when the normal vector is compressed is rare relatively. In this paper, new normal vector compression method which is clustering normal vectors and assigning Representative Normal Vector (RNV) to each cluster and using the angular deviation from actual normal vector is proposed. And, using this new method, Visually Undistinguishable Lossy Compression (VULC) algorithm which distortion of shape model's shading by angular deviation of normal vector cannot be identified visually has been developed. And, being applied to the complicated shape models, this algorithm gave a good effectiveness.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.1954-1961
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• 2008

Microgrid usually consists of a cluster of distributed generators(DGs), energy storage systems and loads, and can operate in the grid-connected mode and the islanded mode. This paper presents detailed descriptions of two different options for controlling the active power of DGs in the microgrid. One is regulating the power injected by the unit to a desired amount(Unit output power control) and the other is to regulate the flow of active power in the feeder where the unit is installed to a constant(Feeder flow control). Frequency-droop characteristics are used to achieve good active power sharing when the microgrid operates in the islanded mode. The change in the frequency and the active power output of DGs are investigated according to the control mode and the configuration of DGs when the microgrid is disconnected from the main grid. From the analysis, this paper proposes a method to determine the droop constant of DGs operating in the feeder flow control mode. Simulation results using the PSCAD/EMTDC are presented to validate the approach, which shows good performance as opposed to the conventional one.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.725-734
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• 2016

For multi-mode radar signals in complex electromagnetic environment, different modes of one emitter tend to be deinterleaved into several emitters, called as "extension", when processing received signals by use of existing sorting methods. The "extension" problem inevitably deteriorates the sorting performance of multi-mode radar signals. In this paper, a novel method based on spatial data mining is presented to address above challenge. Based on theories of data field, we describe the distribution information of feature parameters using potential field, and makes partition clustering of parameter samples according to revealed distribution features. Additionally, an evaluation criterion based on cloud model membership is established to measure the relevance between different cluster-classes, which provides important spatial knowledge for the solution of the "extension" problem. It is shown through numerical simulations that the proposed method is effective on solving the "extension" problem in multi-mode radar signal sorting, and can achieve higher correct sorting rate.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1834-1843
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• 2000

In this paper, we propose a modular neural network based classification method for handwritten numerals utilizing rotated and translated images of an input image. The whole numeral pattern space is divided into smaller spaces which overlap each other and form multiple clusters. On these multiple clusters, multiple multilayer perceptrons (MLP) neural networks, specialized in those clusters, are constructed. Thus, each MLP acts as an expert network on the corresponding cluster. An MLP is also used as a gating network functioning as a mediator among the multiple MLPs. In the learning phase, an input numeral image is dithered by tow geometric operations of translation and rotation so that new numeral images similar to original one are generated. In the recognition phase, we utilize not only input numeral image, but also nearly generated images through the rotation and the translation of the original image. Thus, multiple output values for those generated images were combined to make class decision by various combination methods. The experimental results confirm the validity of the proposed method.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.170-177
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• 2003

Gene expression data are the quantitative measurements of expression levels and ratios of numberous genes in different situations based on microarray image analysis results. The process to draw meaningful information related to genomic diseases and various biological activities from gene expression data is known as gene expression data analysis. In this paper, we present a hierarchical clustering method of gene expression data based on self organizing map which can analyze the clustering result of gene expression data more efficiently. Using our proposed method, we could eliminate the uncertainty of cluster boundary which is the inherited disadvantage of self organizing map and use the visualization function of hierarchical clustering. And, we could process massive data using fast processing speed of self organizing map and interpret the clustering result of self organizing map more efficiently and user-friendly. To verify the efficiency of our proposed algorithm, we performed tests with following 3 data sets, animal feature data set, yeast gene expression data and leukemia gene expression data set. The result demonstrated the feasibility and utility of the proposed clustering algorithm.

• Korean Journal of Food Science and Technology
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• v.23 no.6
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• pp.711-716
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• 1991

Various multivariate statistics were applied to determine the relationships between sensory properties of 9 pre-cooked foods. Twelve sensory terms were selected to differentiate the food samples in stepwise discriminant analysis. Three factors accounted for 61.9% of total variation of 12 sensory attributes detected. Factor I was highly related to the qualitative sensory terms, while factor II to the quantitative ones. The principal component plot made it possible to define the relationships between sensory properties and food samples. In cluster analysis using average linkage and Ward's method, nine pre-cooked foods were classified into three clusters in terms of their sensorial similarities.